使用 Python PIL 的隐写算法

Steganography Algorithm using Python PIL

我正在尝试使用 Python PIL 为黑白图像编写基本的隐写算法。

使用示例图像,我可以成功提取其中的隐藏图像,并隐藏其他图像以随后提取它们。问题在于隐藏文本然后提取它。

代码如下:

from PIL import Image
import matplotlib.pyplot as plt
import scipy.misc as sci
import numpy as np
import array


#CONVERTS IMAGE TO ARRAY OF BINARY 8-BIT NUMBER#
def getImgArray(image):
    w,h = image.size
    out = []
    for x in range(w):
        for y in range(h):
            pixel = image.getpixel((y,x))
            pixel = format(pixel, '08b')
            out.append(pixel)
    return out

def stringByteConverter(data, mode):
    if (mode == "stringToByte"):
        aux = map(ord,data.encode('utf8'))
        aux = [format(char,'08b') for char in aux]
        return aux
    elif (mode == "byteToString"):
        aux = [int(item,2) for item in data]
        aux = "".join(map(chr, aux))
        return aux
    else:
        print("Invalid mode. Use 'stringToByte' or 'byteToString'")

#GETS HIDDEN IMAGE AND RETURNS IT AS BYTE ARRAY REPRESENTING PIXELS#
def getHiddenImage(image):
    buf = ""
    width,height = image.size
    img_aux = []
    for x in range(width):
        for y in range(height):
            if(len(buf)<8):
                pixel = image.getpixel((y,x))
                pixel = format(pixel,'08b')
                buf += pixel[-2:]
            else:
                img_aux.append(buf)
                buf = ""
                pixel = image.getpixel((y,x))
                pixel = format(pixel,'08b')
                buf += pixel[-2:]
    return img_aux

#CONVERT ARRAY OF BYTES TO PNG IMG AND RETURNS PIL IMG OBJECT#
def saveImgArr(ImgArr, size, outputName):
    pixels = np.empty(size)
    iterator = 0
    for i in range(size[0]):
        for j in range(size[1]):
            try:
                pixels[i][j] = int(ImgArr[iterator],2)
                iterator += 1
            except IndexError:
                break

    aux = Image.fromarray(pixels)
    aux = aux.convert("L")
    aux.save(outputName+'.png', 'PNG')
    return pixels

#HIDE IMAGE <src> IN OTHER IMAGE <img>#
def hideImg(src, img, output):
    iterator = 0
    src = src.convert("L")
    srcArr = getImgArray(src)
    imgArr = getImgArray(img)


    for i in range(len(srcArr)):
        buf = []
        buf.append(srcArr[i][:2])
        buf.append(srcArr[i][2:4])
        buf.append(srcArr[i][4:6])
        buf.append(srcArr[i][6:])
        for j in range(4):
            imgArr[iterator] = imgArr[iterator][:-2] + buf[j]
            iterator += 1
    saveImgArr(imgArr,img.size,output)


#HIDE STRING INSIDE IMG#
def hideText(img, string, outputName):
    imgArr = getImgArray(img)
    stringBytes = stringByteConverter(string, "stringToByte")
    iterator = 0
    for i in range(len(string)):
        buf = []
        buf.append(stringBytes[i][:2])
        buf.append(stringBytes[i][2:4])
        buf.append(stringBytes[i][4:6])
        buf.append(stringBytes[i][6:])
        for j in range(4):
            imgArr[iterator] = imgArr[iterator][:-2] + '00'
            imgArr[iterator] = imgArr[iterator][:-2] + buf[j]
            iterator += 1

    print(imgArr[:len(string)*4]) #test print

    saveImgArr(imgArr,img.size,outputName) 

    temp = Image.open(outputName+'.png')
    tempArr = getImgArray(temp)

    print(tempArr[:len(string)*4]) #test print

def getHiddenText(img, msgSize):
    buf = ''
    width,height = img.size
    output = []
    counter = 0
    for x in range(width):
        for y in range(height):
                if(counter < msgSize*4):
                    pixel = img.getpixel((y,x))
                    pixel = format(pixel,'08b')
                    buf += pixel[-2:]
                    counter += 1

    output = stringByteConverter(buf, "byteToString")
    return output

通过在 hideText() 函数中打印数据数组,我能够获得以下内容:

hideText(lena,'test',"lena_hidden_text")

['10100001', '10100011', '10100001', '10100000', '10100001', '10011110', '10100001', '10100001', '10100101', '10100011', '10100000', '10011111', '10011001', '10100011', '10011101', '10011000']

['10011110', '10100000', '10011110', '10011101', '10011110', '10011011', '10011110', '10011110', '10100011', '10100000', '10011101', '10011100', '10010101', '10100000', '10011001', '10010100']

hideText() 调用获得的第一个向量是完全正确的,但是在使用saveImgArr() 保存图像并使用getImgArr() 重新加载之后,返回的第二个向量完全不同。

我这辈子都找不到问题所在。很奇怪,因为使用图像提取隐藏数据或隐藏数据,这两个功能都可以完美地工作。

我只能猜测我处理的文本字节在某种程度上是错误的。任何见解将不胜感激。

在 saveImgArr 中有一件看起来可疑的事情:

aux = Image.fromarray(pixels)
aux = aux.convert("L")

使用的默认 mode for Image.fromarray 是根据输入的数据类型推导出来的。

在您的情况下,输入的数据类型是 numpy 的默认数据类型(浮点数),因此图像将基于浮点数构造。因此,我预测保存的 png 图像看起来不正确(只是一个空白图像,因为每个像素都会饱和到 1.0)。

要更正此问题,您可以向 numpy 提供正确的数据类型,即更改:

 pixels = np.empty(size)

 pixels = np.empty(size,dtype='uint8')

或通过更改 Image.fromarray 显式提供模式:

aux = Image.fromarray(pixels)
aux = aux.convert("L")

aux = Image.fromarray(pixels,mode='L')